Rates of violence in patients classified as high risk by structured risk assessment instruments
TLDR
After controlling for time at risk, the rate of violence in individuals classified as high risk by SRAIs shows substantial variation and assigning predetermined probabilities to future violence risk on the basis of a structured risk assessment is not supported by the current evidence base.Abstract:
Background
Rates of violence in persons identified as high risk by structured risk assessment instruments (SRAIs) are uncertain and frequently unreported by validation studies.
Aims
To analyse the variation in rates of violence in individuals identified as high risk by SRAIs.
Method
A systematic search of databases (1995-2011) was conducted for studies on nine widely used assessment tools. Where violence rates in high-risk groups were not published, these were requested from study authors. Rate information was extracted, and binomial logistic regression was used to study heterogeneity.
Results
Information was collected on 13 045 participants in 57 samples from 47 independent studies. Annualised rates of violence in individuals classified as high risk varied both across and within instruments. Rates were elevated when population rates of violence were higher, when a structured professional judgement instrument was used and when there was a lower proportion of men in a study.
Conclusions
After controlling for time at risk, the rate of violence in individuals classified as high risk by SRAIs shows substantial variation. In the absence of information on local base rates, assigning predetermined probabilities to future violence risk on the basis of a structured risk assessment is not supported by the current evidence base. This underscores the need for caution when such risk estimates are used to influence decisions related to individual liberty and public safety.read more
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References
More filters
Journal ArticleDOI
The measurement of observer agreement for categorical data
J. R. Landis,Gary G. Koch +1 more
TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Book
Judgment Under Uncertainty: Heuristics and Biases
Amos Tversky,Daniel Kahneman +1 more
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Journal ArticleDOI
Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction
TL;DR: The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories.
Journal ArticleDOI
Violent offenders: Appraising and managing risk.
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